code: def residual_unit_v3(
      data, num_filter, stride, dim_match, name, **kwargs
  ):
      """Return ResNet Unit symbol for building ResNet
      Parameters
      ----------
      data : str
          Input data
      num_filter : int
          Number of output channels
      bnf : int
          Bottle neck channels factor with regard to num_filter
      stride : tuple
          Stride used in convolution
      dim_match : Boolean
          True means channel number between input and output is the same, otherwise means differ
      name : str
          Base name of the operators
      workspace : int
          Workspace used in convolution operator
      """
      bn_mom = kwargs.get("bn_mom", 0.9)
      workspace = kwargs.get("workspace", 256)
      memonger = kwargs.get("memonger", False)
      # print('in unit3')
      bn1 = mx.sym.BatchNorm(
          data=data,
          fix_gamma=False,
          eps=2e-5,
          momentum=bn_mom,
          name=name + "_bn1",
      )
      conv1 = Conv(
          data=bn1,
          num_filter=num_filter,
          kernel=(3, 3),
          stride=(1, 1),
          pad=(1, 1),
          no_bias=True,
          workspace=workspace,
          name=name + "_conv1",
      )
      bn2 = mx.sym.BatchNorm(
          data=conv1,
          fix_gamma=False,
          eps=2e-5,
          momentum=bn_mom,
          name=name + "_bn2",
      )
      act1 = Act(
          data=bn2, act_type=config.net_act, name=name + "_relu1"
      )
      conv2 = Conv(
          data=act1,
          num_filter=num_filter,
          kernel=(3, 3),
          stride=stride,
          pad=(1, 1),
          no_bias=True,
          workspace=workspace,
          name=name + "_conv2",
      )
      bn3 = mx.sym.BatchNorm(
          data=conv2,
          fix_gamma=False,
          eps=2e-5,
          momentum=bn_mom,
          name=name + "_bn3",
      )
  
      if dim_match:
          shortcut = data
      else:
          conv1sc = Conv(
              data=data,
              num_filter=num_filter,
              kernel=(1, 1),
              stride=stride,
              no_bias=True,
              workspace=workspace,
              name=name + "_conv1sc",
          )
          shortcut = mx.sym.BatchNorm(
              data=conv1sc,
              fix_gamma=False,
              momentum=bn_mom,
              eps=2e-5,
              name=name + "_sc",
          )
      if memonger:
          shortcut._set_attr(mirror_stage="True")
      return bn3 + shortcut
  
file_path: insightface/recognition/partial_fc/mxnet/symbol/symbol_utils.py
imports: import sys
  import os
  import mxnet
  from default import config
label_desc: Use image node_id 5 for calling a global function with example usage: residual_unit_v3(data, num_filter, stride, dim_match, name) and returns: unknown